Pore Image Processor
- Includes installation and usage instructions (newer features not yet documented).
- Maximized the image display size.
- Several small tweaks to the image display and resizing system so that changing window sizes should be handled more smoothly.
- Roundness Index added and extraneous recalculation removed (2009-04-24)
- Added a simple Roundness Index which is calculated simply as the Minor axis/Major axis. This property has been added to the results table and the pore data structure (results.pores(i)).RoundnessIndex has the roundness index for the ith pore). Roundness has also been added to the list of properties which can be used as a cutoff to remove many pores. For example, it is possible to remove all pores with a Roundness index less than 0.5.
- Also updated so that pore removal no longer automatically recalculates results. This saves extraneous calculations if there are several pore removals in a row, but introduces the problem that the results can get out of sync (e.g. the mean pore size, etc., include the eliminated pores). To remind the user that the results should be recalculated before they are used or saved, the 'Update Results' button turns red if the results are out of sync and need to be refreshed. In addition, if a user tries to save a results file before recalculating, a dialog box warns them that this is the case.
- After pore removal the view now defaults to the background-corrected image.
- Intensity cutoff added (2008-10-05)
- Adds measurement of average pore intensity (measured in the background-corrected image), and adds the ability to remove pores based on this property also. Access to this feature is from the results control panel. In saved results, the average intensity for the ith pore can be found in results.pores(i).avg_intensity, while the mean and standard deviation of average intensities for all pores can be found in results.stats.mean_avg_intensity and results.stats.std_avg_intensity.
- In addition, pores which cross the image boundary are now treated more appropriately in calculations. Their area is included in porosity calculations and their intensity is included in mean avg_intensity calculations, but their areas, diameters, and major and minor axes are not included in overall means since these numbers will not be accurate. Edge pores count as 1/2 pore for the pore density calculation. Pores identified as edge pores are outlined in green rather than red when pore boundaries are shown.
- Size cutoff added (2008-08-11)
- Allows removal of pores by size cutoff in area, diameter, and major or minor axes, specifying cutoff in either nanometers or pixels. Access to this feature is from the results control panel.
- Calibration selection added (2008-07-23)
- Allows selection of pixels/nm calibration by microscope and magnification when calculating results.
- Minor bug fix (2008-07-16)
- Fixed image save using 'i' key.
- Calculates and makes a histogram of the contributed area that a particular pore size makes, normalized by the image area (by default), or the total area of all pores, returning area fractions and edges.
- Plots a histogram of pore data based on a results structure generated by Pore Image Processor. The user can supply a results structure as the first input, the number of desired histgram bins as the second input, and the desired pore property to plot as the third input, or can leave any inputs empty to use defaults (prompt user to select results file; 50 bins; pore equivalent diameters).
- A file that calculates flow and permeability from the Tong equation using porosity, average pore size, thickness and pressure as inputs. Type
help TongEqin MATLAB for usage. Uses .dat file from PIP as input.
- Fixed pore distribution histogram calculation.
- Endothelial vacuolization induced by highly permeable silicon membranes. Acta Biomater. 10, 4670-7. (2014 Nov 01).
- Nanoporous silicon nitride membranes fabricated from porous nanocrystalline silicon templates. Nanoscale. 6, 10798-805. (2014 Sep 21).
- Highly permeable silicon membranes for shear free chemotaxis and rapid cell labeling. Lab Chip. 14, 2456-68. (2014 Jul 21).